Trading card sorter and methods

ABSTRACT

A sorter processes trading cards in an affordable, accurate, and easy-to-use manner. The sorter includes an input and output bin. A transport path moves cards between the bins and has two scan bars, one above and one below the path. The scan bars capture an image of a top and bottom surface of ones of the cards. A controller coordinates movement of the cards along the path and receives the image for processing. Users interact with the controller by way of an interface to influence the processing. The sorter also includes a coil to detect metal foil on the cards. Other embodiments are envisioned.

This application claims priority as a continuation application of U.S.Ser. No. 17/683,809, filed Mar. 1, 2022, having the same title.

FIELD OF THE INVENTION

The present disclosure relates to methods and apparatus involvingtrading cards, such as gaming and collectible trading cards. It relatesfurther to identifying, inventorying, sorting, and grading tradingcards, to name a few. It also relates to providing individuals andretail establishments with an affordable, accurate, and easy-to-useportable device for managing their cards.

BACKGROUND

As trading card games have grown over the past twenty-five years, so toohas the number of cards that players and retail stores find themselvesmanaging. Often, both the players of these games, and the stores thatbuy, trade, and resell cards, find themselves inundated with managingthousands or in some cases millions of cards. Every year, too, thevolume of cards grows as games involving the cards add new and variedcards to keep fresh the gameplay and entice more entrants and collectorsinto the market. In turn, a large secondary market exists for buying,trading, and selling individual cards. Knowing exactly which cards existin inventory becomes profitable for individuals and can help duringgameplay as having specific card combinations allow users to performbetter. There exists, then, a need for players and stores that buy,sell, and trade these cards to efficiently inventory, sort, and managelarge and varied card collections.

Currently, the marketplace has smart phone apps that utilize cameras ofthe phones to inventory cards one by one. In testing, the inventorsfound these apps slow as users must manually manipulate the cardsone-by-one. The inventors also found these apps reliant on the cameraquality of the phone, which varies dramatically from phone to phone, andbackground lighting sometimes makes for poor accuracy in identifyingindividual cards. The marketplace also has companies that sell hardwarethat identifies, inventories, and sorts cards. Two of the most prevalenthardware devices use camera-based detection, along with an armature andsuction cup to sort the cards. The inventors, however, found the cameraarrangements capable of only allowing viewing of cards but on a singularside of the card which forces users to presort by hand all cards intosimilar orientations, e.g., face-up. The inventors also found exorbitantprices for hardware ranging from many thousands of dollars to dozens ofthousands of dollars. There exists, then, a further need for anaffordable, accurate, and easy-to-use device to help individuals andstores to manage their trading card inventories.

Yet, any devices in the marketplace must further contemplate the carefulhandling of individual cards during sorting, as mishandled cards canbecome damaged and lose their valuation. As is known, the condition oftrading cards is often assessed professionally, such as by theProfessional Sports Authenticator (PSA). Current grading standards bythe PSA range from 1 (Poor) to 10 (Gem Mint). A 10 (Gem Mint) ratingcard is described as “a virtually perfect card” that includes “fourperfectly sharp corners, sharp focus and full original gloss.” A 9(Mint) rating card, on the other hand, is described as “a superbcondition card that exhibits only one of the following minor flaws: avery slight wax stain on reverse, a minor printing imperfection orslightly off-white border.” The difference of condition of but one pointin the condition of a card can greatly affect its market value. Forexample, the card “Blue-Eyes White Dragon” from the 2002 Starter DeckKaiba of the Yu-Gi-Oh! TCG has an estimated value of $80 for a 9 ratingand $350 for a 10 rating(https://www.psacard.com/smrpriceguide/non-sports-tcg-card-values/2002-yu-gi-oh-starter-deck-kaiba/2885,May 5, 2020). Therefore, even the slightest mishandling of a card duringidentifying and sorting can have a severe impact on card value andappeal. The inventors recognize a further need to avoid mishandling anddamaging cards during processing.

SUMMARY

The foregoing and other problems are solved with a sorter that processestrading cards in an affordable, accurate, and easy-to-use manner. Thesorter includes an input and output bin. A transport path moves cardsbetween the bins and has two scan bars, one above and one below thepath. The scan bars capture an image of a top and bottom surface of onesof the cards. A controller coordinates movement of the cards along thepath and receives the image for processing. Users interact with thecontroller by way of an interface to influence the processing. Thesorter also includes a coil to detect metal foil on the cards.

Other embodiments contemplate: a removable input tower to make it easyto swap new stacks of cards; feeding cards from a top of the stack usingan elevating mechanism (could be spring loaded, or motor controlled);feeding cards from the bottom of the stack (the stack could be verticalor angled depending on the capacity necessary and the physical sizerequirements); and or feeding single or multiple stacks of cards.

For card picking, separating, and transporting cards, variousembodiments envision: a pick roller mechanism for feeding cards from thetop of a stack; one or more friction rollers for feeding cards from thebottom of a stack; a suction cup mechanism for lifting cards from thetop of a stack; a mobile arm to move cards from one location to another;a transport belt to move cards during processing; pairs of nip rollersto move cards during transport; and or transporting cards via gravity onan angled surface.

Card imaging and recognition embodiments envision one or more of thefollowing: a collimated laser or other sensor to measure the physicaldimensions and shapes of cards; a smart phone interfacing with thesorter; a gloss sensor to detect glossy surfaces on cards; and or aninductive sensor to detect if cards have metal foil or not.

Card output and sorting embodiments include or not: single or multiplebins; output bins affixed to the sorter or removable; a dual-purpose binacting as both an input and output bin; an output bin that doubles as astorage box for cards; sorting cards with a moving diverter; sortingcards with speed-adjusted rollers; sorting cards with a moving armature,including a single or multiple axis of movement; and or sorting cardswith a moving and tiltable table.

Other embodiments are possible.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagrammatic view of a sorter for trading cards;

FIG. 2 is a cutaway view of a sorter for trading cards;

FIG. 3 is a diagrammatic view of rollers to pick trading cards from aninput bin;

FIG. 4 is a partial diagrammatic view of a transport path for tradingcards in a sorter, including a pair of roller nips;

FIG. 5 is a partial view of a sorter having multiple output bins fortrading cards;

FIG. 6 is a cutaway view of a sorter for trading cards in an alternateembodiment;

FIG. 7 is a cutaway view of a sorter having multiple output bins fortrading cards;

FIGS. 8A and 8B are partial views of a sorter having a diverter fordirecting trading cards to multiple output bins;

FIGS. 9A, 9B, 9C, and 9D are partial views of a sorter having anarmature for directing trading cards to multiple output bins;

FIGS. 10A, 10B, 10C, and 10D are partial views of an armature fordirecting trading cards to multiple output bins;

FIG. 11 is a diagrammatic view of a foil detection sensor for detectingin a sorter trading cards with metal foil;

FIG. 12 is a diagram of representative pixels of a scanned image of asurface of a card and a hash therefor; and

FIG. 13 is a flowchart for one embodiment of matching scanned images ofcards versus scanned images of reference cards, and sorting thereby.

DETAILED DESCRIPTION

In the following detailed description, reference is made to theaccompanying drawings wherein like numerals represent like details. Theembodiments are described in sufficient detail to enable those skilledin the art to practice the invention. It is to be understood that otherembodiments may be utilized and that changes may be made withoutdeparting from the scope of the invention. The following detaileddescription, therefore, is not to be taken in a limiting sense and thescope of the invention is only defined by the appended claims and theirequivalents.

With reference to FIG. 1 , a sorter 10 for trading cards includes ahousing 11 that is portable for ease of placement by users. An input bin12 receives the cards from the users and an output bin 14 is providedfor depositing the cards after processing by a controller, C. Theprocessing is any of a variety, such as identifying cards, gradingcards, valuing cards, sorting cards by gameplay, random shuffling ofcards, sorting cards by color, building decks of cards, arranging cardsby face-up/-down orientation, or the like. The controller is also any ofa variety, but typifies an ASIC(s), circuit(s), microprocessor(s),firmware, software, or the like. Users interact with the processing ofcards by the controller via a user interface 16. By extension, the userinterface may include computing connections, such as WiFi connection toa smart phone 18 and/or a wired, wireless connection to a computingnetwork typified by a server 20 in a cloud environment 22 alsoaccessible to the controller, C. A local or remote memory M furtheraccompanies the controller in order to conduct processing. Similarly, alocal or remote database is available to the controller, such as may bestored on the server, for accessing relevant information for processing.The controller and sorter 10 receive power by way of a traditional plug24 connected to a power source 26.

With reference to FIG. 2 , a cutaway view of the sorter 10 reveals innermechanical structures of the sorter. Among them, each of the input andoutput bins 12, 14 include a bottom 12′, 14′, to stack thereon thetrading cards for processing. Ones of the cards travel from the bottom12′ of the input bin 12 to the output bin 14 along a transport path,given generally as dashed line 30. Along the path, a friction roller 32rotates in the direction of arrow A to pick cards from the bottom of theinput bin to start the travel of the cards from the input to the outputbin. The roller 32 is preferably covered in rubber R to prevent damageto the trading cards as the roller rotates. The roller is also raised toprevent the cards from rubbing on stationary surfaces. The roller couldbe singular in design and/or exemplify a plurality of such rollers.(FIG. 3 depicts a simplified breakaway view of the sorter showing aplurality of friction rollers 32, 32′ coated in rubber, R).

Further along the path exists two scan bars 34, 36 with one 36 of thetwo scan bars above the transport path 30 and the other 34 of the twoscan bars below the transport path. During use, the scan bars scan animage of a top surface 42 (FIG. 4 , simplified transport path 30depicted) and a bottom surface 44 (FIG. 4 ) of the ones of the tradingcards 40 (FIG. 4 ) as the ones of the trading cards travel past the twoscan bars along the transport path during use. The scanned image isprovided to the controller C for processing. The scan bars extendwidthwise over an entirety of the surfaces of the cards. That the twoscan bars obtain dual-sided images of each card, the cards in the inputbin can be oriented in either face-up/-down orientation without issueduring processing. The controller also coordinates a timing of movementof the friction roller and initiation of the scanning by the scan bars.A sensor 50 facilitates this by optically sensing a leading edge 46(FIG. 4 ) and/or a trailing edge 48 (FIG. 4 ) of the cards, which may beone and the same sensor, or separate from one another, to indicate tothe controller to start/stop scanning by the scan bars. A pair of rollernips 58, 58′ on either side of the two scan bars 34, 36 along thetransport path are provided for driving the trading cards along thetransport path. As seen in the simplified view in FIG. 4 , a singlemotor M rotates the pair of roller nips 58, 58′ at a same speedcoordinated by the controller C. In this way, the cards process withoutbuckling or stretching. A rail 60 may also exist between the roller nipsto keep at a same height along the transport path a leading edge of thetrading cards and the roller nips to prevent damage to the cards duringtransit. In distance, the nips are spaced slightly farther apart than alength (1) of a standard trading card. The speed of the motor driven bythe controller can be any of a variety, but one embodiment envisionsdriving the motor at a speed such that a card processing along thetransport path 30 has enough momentum to move from the proximate nip tothe distal nip without falling.

In various alternate embodiments, a removable tower 12-1 is envisionedin FIG. 2 for placement on the housing 11 for vertically holdingadditional trading cards for dropping into the input bin 12. The outputbin may also include a removable chute 14-1 that moves in the directionof arrow B for access to the trading cards having been processed by thecontroller. With reference to FIG. 5 , a sorter may have a plurality ofoutput bins 14-2, 14-3 for trading cards sorted from a single input bin12. In a front view of the sorter of FIG. 5 , FIG. 6 shows the sorter incutaway having two friction rollers 32, 32′ for picking cards 40 fromthe input bin 12 for processing by the controller and, ultimately, fordepositing in the output bin 14-2. The output bin may also have anon-contact, flush mounted optical sensor 60 for sensing a fullcondition of the cards 40 in the bin. FIG. 7 shows the two output bins14-2, 14-3 in cross section of FIG. 5 along line 7-7. To sort the cards40 into either of the output bins, a diverter 75 is given in FIGS. 8Aand 8B. In FIG. 8A, the diverter 75 is positioned upward such that aprocessed trading card 40-A hits an underside 75-U along path 80A andfalls into the output bin 14A. In FIG. 8B, the diverter 75 is positioneddownward such that a processed card 40-B travels above the topside 75-Tof the diverter along path 80B and bypasses output bin 14A and travelsto a second output bin (not shown in this view).

In lieu of a diverter, the sorter may include a shifting armature fordepositing processed cards in the output bins. By comparing FIGS. 9A-9D,a shifting armature slides S back and forth above the output bins 14-2,14-3. In FIG. 9A, the armature 90 slides above output bin 14-2 and abottom 90-O opens in FIG. 9B so that a card processed by the controllercan be dropped into output bin 14-2. Similarly, in FIG. 9C, the armature90 slides above output bin 14-3 and the bottom 90-0 opens in FIG. 9D sothat a card processed by the controller can be deposited into the outputbin 14-3.

In the simplified views of FIGS. 10A-10D, the armature 90 (FIG. 10A)opens whereby two halves 90-1, 90-2 (FIG. 10B) simultaneously move awayfrom the card 40 in the direction of the arrows and gravity, g, dropsthe card into an output bin. In FIG. 10C, the armature 90 can inducerotation into the card 40, such that if the sorter detects that a cardis not facing the direction chosen by the user, the armature can be usedto flip the card. By delaying movement of one of the halves of thearmature, a rotation can be induced. In FIG. 10C, halve 90-1 moves awayfrom the card 40 first, whereas halve 90-2 moves away from the card 40second (FIG. 10D), thereby inducing a rotation in the card as seen bythe arrows. The controller induces this behavior using a customalgorithm that, artisans will appreciate, is dependent on a stack heightof the cards in a current output bin as well as the width of a givencard to-be-rotated. Thus, the controller accounts for this by trackinghow many cards have been deposited into each of the output bins and, byway of scanning of the cards with the dual can bars, knowing the size ofthe card.

With reference to FIG. 11 , artisans will appreciate that many tradingcards 40 have metal or foil 90 over an entirety of the card or invarious sections 95 thereof, as shown. Thus, the sorter further includesa foil detection sensor 100 in the transport path as cards travel fromthe input to output bins. In one embodiment, the sensor has one or moreplanar coils 101 disposed on a printed circuit board (PCB) paired with atuning capacitor (not shown). As is known, there exists a naturalresonant frequency of the coils which is determined by the inductance ofthe coil (L), the tuning capacitance combined with the parasitic coilcapacitance (C), and the resistance of the coil traces (R). During use,the tuned coil is connected to an off-the-shelf IC coordinated by thecontroller which both establishes a resonant excitation in the coil andmeasures the natural resonant frequency. The excitation produces an ACcurrent in the coil which in turn creates an AC magnetic field. When aconductive object (in this case a foil 90 layer embedded in a tradingcard 40) is in the vicinity of the coil, the AC magnetic field createsan emf (electromotive force) which generates a current in the conductiveobject. From Faraday's Law, the current (referred to as an eddy current)creates a magnetic field, which tends to oppose the original magneticfield, and manifests itself as a decrease in the inductance of the tunedcoil. Furthermore, any heating which may occur in the conductive objectdue to this eddy current manifests itself as an increase in theresistance R of the coil. Additionally, any capacity of the conductiveobject to store magnetic energy (its permeability) will manifest itselfas an increase in the effective L of the coil. Due to the combination ofthese three effects, the resonant frequency of the tuned coil willshift. If the shift in resonant frequency is significant enough, the ICwill toggle the state of a digital output. This indicates to thecontroller that a conductive object (the card having foil) is in thevicinity of the coil, thus detecting or not a card with foil. In afurther embodiment, foil detection sensor 100 can be used to read binaryinformation 103 of the card in the form of 1's and 0's by being placedadjacent to the card and the presence or not of metal on the card 40indicates a binary 1 or 0, or vice versa. The form factor of the sensor,of course, can be modified to add or subtract a number of coils 101allowing more or less data to be read over the surface of a card 40according to sections 95 of foil. The binary information could be alsoused to authenticate trading cards.

While the sensor 100 can detect metal foil, the controller canadditionally include optical character recognition (OCR) for regions ofcards to further help with identification of the cards. That is, somecards include information on their surfaces indicating set names, cardnumbers within that set, and codes that determine the language of thecard. While not all cards have this information, OCR will help provideinformation about the cards on those that do. In still otherembodiments, a convolution neural network could be established for thecontroller and trained to detect all the various types of trading cardsas users feed images of cards having been captured and labeled to buildup a training set. In either, once a card has been recognized by thecontroller, that information is added to a database comprising the restof the cards in a collection of cards held by the user.

In any embodiment, the controller receives from the dual scan bars thescanned image of top and bottom surfaces of ones of the cards. Accordingto a combination of edge detection, image rotation, and image cropping,each card processed by the controller is isolated from the backgroundlayer of the card. A hashing algorithm is then executed by thecontroller that generates a first set of hashes from each scanned imageafter cropping out the borders of cards and followed, next, bydownscaling each scanned image (sans the border) to 32×32 pixels. Inorder to generate each hash, a discrete cosine transform is used

${X_{k} = {{\sum\limits_{n = 0}^{N - 1}{x_{n}{\cos\left\lbrack {\frac{\pi}{N}\left( {n + \frac{1}{2}} \right)k} \right\rbrack}k}} = 0}},\ldots,{N - 1.}$

and applied to groupings of rows and columns of pixels of the scannedimage. The hash occurs first in an upper left 8×8 grid of the pixels110, as seen in FIG. 12 , whereby a mean pixel value is calculated fromthe grid. In turn, a new binary map is generated by comparing each pixelvalue of the grid to the mean and assigning it a “1” if the pixel valueis greater than the mean and a “0” otherwise. The hash continues in thisfashion first from the upper left grid of pixels, then working acrossthe 32×32 pixels and down to the bottom right, recording each 1 or 0 togenerate a 64-bit perceptual hash representing the scanned image, e.g.,pHash (FIG. 12 ). With few exceptions, cards within a trading card gameall share a common backside which identifies the game to which theybelong. As such, the pHash per card is then applied to reference imagesof the backsides of cards of each card game by exclusive or'ing them(XOR) to reveal a Hamming Distance. Those with the smallest HammingDistance are then chosen as the best selection, or match of a scannedcard (provided the distance meets a closeness threshold). The followingis provided as an example, whereby the “Ferret Scan Hash” represents thepHash of bottom surface of a scanned card in the sorter and theReference Hash represent the pHash of a “Magic the Gathering” card andthe resulting Hamming Distance between the two is eight (8), therebyidentifying the scanned card as a Magic the Gathering card.

 Reference hash: 1000 1001 1010 1111 0001 1111 1111 0111 0011 1111 10010111 0111 1101 1111 1111 Ferret Scan hash: 1000 0000 1011 1111 0010 11111111 0111 0011 1111 1101 0111 0111 1100 1111 0111   XOR: 0000 1001 00010000 0011 0000 0000 0000 0000 0000 0100 0000 0000 0001 0000 1000   Hamming Distance = 8

It should be noted that a pHash is not rotation invariant, meaning thatan inverted scanned image will generate a different hash value than acard having a different orientation. In turn, the controller comparesscanned cards against not only backsides of trading card games, but alsoto those same backsides if inverted. Then, if an inverted back ismatched, the correct orientation of the card can be determinedregardless of which direction or side is facing up during processing.Regardless, once the backside of the scanned image of a card has beenidentified, the top surface of the corresponding image from the dualscan bars can be also perceptually hashed, e.g., pHash, to provide aperceptual hash for each of the top and bottom surface of the cards soscanned by the sorter.

The controller also generates a gradient hash (dHash). In oneembodiment, this includes downscaling the scanned image of a surface ofthe card to an 8×8 grid of pixels. An 8×8 binary map is then createdbeginning with a second column of the pixels and setting each value to 1if greater than its neighbor on the left or a 0 otherwise. From there,the gradient hash is generated in the same manner as the perceptualhash, e.g., beginning with the top left position of the pixels andworking across and down to the bottom right, recording each 1 or 0 togenerate a 64-bit dHash representing the scanned image. Comparisons ofthe dHash are then compared to gradient hashes of the reference images.Ultimately, matches are selected within a certain threshold of pHashvalues as compared against dHash values. This step is used becausetrading cards may share similar frequency information despite havingdifferent images. That the gradient hash dHash generated for a givenscanned image is significantly different than the perceptual hash pHashfor a given other-side surface of a card, this comparison increases theconfidence that the closest match to both the perceptual and gradienthashes is the correct one.

As several trading card games include different cards with similarartwork, and reprinted cards in different editions have only slightdifferences from one another, a high degree of confidence in matchingscanned cards to reference cards is obtained if the controller obtainsmultiple matches for its scanned cards in relation to the referencecards. Thus, the flowchart 120 of FIG. 13 shows but one technique thecontroller executes per the perceptual and gradient hashes obtained fromthe tops and bottom surfaces of the scanned cards relative to thedatabase (DB) of reference cards.

The foregoing illustrates various aspects of the present disclosure. Itis not intended to be exhaustive. Rather, it is chosen to describe theprinciples of the present disclosure and its practical application toenable one of ordinary skill in the art to utilize the presentdisclosure, including its various modifications that naturally follow.All modifications and variations are contemplated within the scope ofthe present disclosure as determined by the appended claims. Relativelyapparent modifications include combining one or more features of variousembodiments with features of other embodiments.

1. A method for sorting trading cards, comprising: establishing acomputing connection between a controller of a card sorter and a smartphone; imaging top and bottom surfaces of a plurality of trading cardsin the card sorter; comparing results of the imaging to stored data in alocal or remote database available to the controller; and providing tothe smart phone results of the comparing.
 2. The method of claim 1,further including determining a quality grade of each of the pluralityof trading cards.
 3. The method of claim 1, further includingestablishing a computing connection between the controller and a server.4. The method of claim 1, further including scanning with two scan barsthe plurality of trading cards from above and below the plurality oftrading cards.
 5. The method of claim 1, further including identifyingeach of the plurality of scan cards.
 6. The method of claim 1, furtherincluding sorting the plurality of scan cards according to predefinedcriteria and providing the sorting to the smart phone.
 7. The method ofclaim 1, further including determining whether any of the plurality oftrading cards include metal foil.
 8. The method of claim 1, furtherincluding depositing the plurality of trading cards into at least twooutput bins of the card sorter.
 9. The method of claim 1, furtherincluding converting to pixels each of the plurality of trading cards.10. The method of claim 9, further including executing a hash of valuescorresponding to the pixels.
 11. The method of claim 10, furtherincluding searching a database of matches for the hash of values. 12.The method of claim 1, further including transporting the plurality oftrading cards along a transport path from an input to an output bin. 13.A method for sorting trading cards, comprising: providing a userinterface for a card sorter; imaging with two scan bars in the cardsorter along a transport path top and bottom surfaces of a plurality oftrading cards in the card sorter; comparing results of the imaging tostored data in a local or remote database available to a controller ofthe card sorter; and providing to the user interface results of thecomparing.
 14. The method of claim 13, further including establishing acomputing connection between the controller and a smart phone.
 15. Themethod of claim 13, further including determining a quality grade ofeach of the plurality of trading cards based on the comparing andproviding same to the user interface.
 16. The method of claim 13,further including establishing a computing connection between thecontroller and a server for said comparing.
 17. The method of claim 13,further including sorting the plurality of scan cards according topredefined criteria and providing results of the sorting to the userinterface.
 18. The method of claim 17, further including depositing theplurality of trading cards into at least two output bins of the cardsorter.
 19. The method of claim 13, further including converting topixels each of the plurality of trading cards based on the imaging andexecuting a hash of values corresponding to the pixels.
 20. The methodof claim 19, further including searching a database of matches for thehash of values.